A. Manoj

A deep learning perception framework for farm digital twins: weed species classification, semantic segmentation, and gradient-based visual interpretability

This paper presents a tri-component deep learning framework designed explicitly as a perception and interpretability layer for Farm Digital Twin architectures, evaluated on a five-species balanced subset of the Moving Fields Weed Dataset (MFWD)—a publicly available benchmark of 94K high-resolution images of 28 weed spe...